wav2vec2-Y_speed2

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.9944
  • Cer: 38.7688

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer
43.7135 0.1289 200 5.1032 100.0
5.0439 0.2579 400 4.6765 100.0
4.8774 0.3868 600 4.6557 100.0
4.8641 0.5158 800 4.6426 100.0
4.7995 0.6447 1000 4.6472 100.0
4.7762 0.7737 1200 4.6153 100.0
4.7579 0.9026 1400 4.6154 100.0
4.7082 1.0316 1600 4.6180 100.0
4.6786 1.1605 1800 4.5371 100.0
4.6438 1.2895 2000 4.5289 100.0
4.5663 1.4184 2200 4.4416 100.0
4.503 1.5474 2400 4.3983 99.3421
4.2564 1.6763 2600 4.0853 82.7714
3.7092 1.8053 2800 3.2871 61.8656
3.071 1.9342 3000 2.9127 53.0663
2.704 2.0632 3200 2.6764 49.4302
2.4656 2.1921 3400 2.4448 45.2420
2.2855 2.3211 3600 2.2835 42.6339
2.1728 2.4500 3800 2.2042 42.0876
2.0623 2.5790 4000 2.1021 39.8144
1.9909 2.7079 4200 2.0544 39.5266
1.9129 2.8369 4400 2.0083 38.7453
1.9151 2.9658 4600 1.9944 38.7688

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.5.0+cu121
  • Datasets 3.1.0
  • Tokenizers 0.19.1
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